Measuring the geometric, kinematic and dynamic characteristics of oceanic wave breaking
File(s)
Author(s)
Peach, Joseph
Type
Thesis
Abstract
Sea surface wave breaking is the dominant process resulting in the dissipation of ocean surface wave energy. During breaking, wave energy is converted into turbulent kinetic energy, and if breaking is significantly energetic, entrains air which facilitates air-sea gas transfer and scatters light, creating the signature whitecap. Exploiting the broadband scattering of light by the surface whitecaps, this study uses a fixed stereo imaging system to develop the Automated Whitecap Detection And Tracking algorithm (AWDAT) to detect and track individual air-entraining surface breaking waves.
AWDAT incorporates novel methods for handling complex foam patch evolution, including splitting and merging, enabling detailed analysis of large observational datasets from the Acqua Alta Oceanographic Tower. Using data processed with AWDAT, this research investigates the relationship between the Phillips breaking crest length distribution ($\Lambda(c_b)$) and growth whitecap foam coverage ($W_g$). The study also systematically quantifies the impact of perspective distortion inherent in non-nadir stereo imagery on derived whitecap statistics.
Methods for measuring event-based breaking speed and crest length were refined, revealing a scale-dependence in the initial breaking speed relative to the event mean. The timescale $\tau_{\Lambda}$ connecting $W_g$ and $\Lambda(c_b)$ is empirically derived, incorporating the influence of quantified whitecap flocculence.
Analysis of perspective distortion from tilted camera systems reveals that bulk rates, such as total energy dissipation and air entrainment, are relatively insensitive to perspective effects due to the dominance of large, easily detected events. Conversely, the shapes of statistical distributions for scale-dependent properties are measurably affected by distance-dependent detection limits.
This work provides a validated automated analysis tool (AWDAT) for the oceanographic community, advances understanding of wave breaking dynamics through refined parameter measurements and demonstrated $\tau_{\Lambda}$ scaling, and offers quantitative guidance on perspective bias in stereo-imaging studies. These contributions support improved parameterisations of wave breaking and its effects in wave and climate models.
AWDAT incorporates novel methods for handling complex foam patch evolution, including splitting and merging, enabling detailed analysis of large observational datasets from the Acqua Alta Oceanographic Tower. Using data processed with AWDAT, this research investigates the relationship between the Phillips breaking crest length distribution ($\Lambda(c_b)$) and growth whitecap foam coverage ($W_g$). The study also systematically quantifies the impact of perspective distortion inherent in non-nadir stereo imagery on derived whitecap statistics.
Methods for measuring event-based breaking speed and crest length were refined, revealing a scale-dependence in the initial breaking speed relative to the event mean. The timescale $\tau_{\Lambda}$ connecting $W_g$ and $\Lambda(c_b)$ is empirically derived, incorporating the influence of quantified whitecap flocculence.
Analysis of perspective distortion from tilted camera systems reveals that bulk rates, such as total energy dissipation and air entrainment, are relatively insensitive to perspective effects due to the dominance of large, easily detected events. Conversely, the shapes of statistical distributions for scale-dependent properties are measurably affected by distance-dependent detection limits.
This work provides a validated automated analysis tool (AWDAT) for the oceanographic community, advances understanding of wave breaking dynamics through refined parameter measurements and demonstrated $\tau_{\Lambda}$ scaling, and offers quantitative guidance on perspective bias in stereo-imaging studies. These contributions support improved parameterisations of wave breaking and its effects in wave and climate models.
Version
Open Access
Date Issued
2025-05-31
Date Awarded
2025-10-01
Copyright Statement
Attribution-NonCommercial 4.0 International Licence (CC BY-NC)
License URL
Advisor
Callaghan, Adrian
Sponsor
Natural Environment Research Council (Great Britain)
Grantham Institute
Publisher Department
Department of Civil and Environmental Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)